title: GASCO: genetic algorithm simulation for codon optimization.
abstract: Codon optimization is a generic technique to achieve optimum expression of a foreign gene in the host's cell system. Selection of optimum codons depends on codon usage of the host genome and the presence of several desirable and undesirable sequence motifs. Searching these motifs in all possible combinations of the codons increases the search space exponentially with respect to sequence length. GASCO is an algorithm developed for the optimum codon selection using genetic algorithms. The algorithm reduces the search space and provides an approximate solution to the problem. The algorithm has applications in DNA vaccine design for successfully eliciting potent immune responses and synthetic gene design for metabolic pathway engineering. The software for the proposed algorithm is available on http://miracle.igib.res.in/gasco/.
authors.affiliation: GN Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi, India. kuljeet.singh@ebc.uu.se
authors.forename: Kuljeet Singh
authors.initials: KS
authors.lastname: Sandhu
authors.forename: Sunil
authors.initials: S
authors.lastname: Pandey
authors.forename: Souvik
authors.initials: S
authors.lastname: Maiti
authors.forename: Beena
authors.initials: B
authors.lastname: Pillai
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D003062:Codon / Q000235:genetics*; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D020407:Internet; D010363:Pattern Recognition, Automated / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D003062:Codon